Atmospheric Sciences & Global Change Staff Awards & Honors

Yun Qian Directed International Workshop

Topic Addresses Uncertainty Quantification in Climate Modeling

Dr. Yun
Qian, atmospheric and climate modeling scientist at Pacific Northwest
National Laboratory, was invited to organize and direct an international
workshop on "Uncertainty
Quantification in Climate Modeling and Projection" in Trieste, Italy. Drawing
on international interest nearly 70 scientists and students from some 30
countries around the world attended the five-day workshop at the Abdus Salam
International Centre for Theoretical Physics (ICTP) in mid-July 2015.

Predicting climate change is one of the most complex
problems facing scientists who have been striving to understand climate system
behavior and improve Earth system models for years. The overall uncertainty in climate
projections, however, remains relatively unchanged. As climate models become
increasingly complex, it becomes extremely challenging to reduce uncertainty.

Accurately interpreting climate simulations and quantifying
uncertainty is a key to understanding and accurately modeling atmospheric,
land, ocean, and socio-economic phenomena and processes. Communities must rely
on the accuracy of climate models to prepare for and adapt to potential climate
change scenarios. Such information should include both well-characterized and
well-quantified uncertainty.

The UQ workshop underscored the importance of recognizing
and quantifying uncertainty in climate models to enhance the validation of climate
projections and impact assessments. Many underdeveloped nations lack the
infrastructure and resources to recover physically and economically from climate-change
extremes, such as storms, drought and other natural disasters. For this reason,
UNESCO provided funding to bring 30 representatives to the workshop from countries
in Africa, Asia and South America whose populations are especially vulnerable
to the effects of climate change.

In such nations, support for basic water and energy needs is
a challenge. Often their population centers are located near bodies of water
where unexpected flooding and other weather-related events can destroy property
and threaten lives. Fragile energy facilities, public utilities and ecosystems
are also frequently vulnerable to weather extremes and the impacts of climate
change.

As research leaders in developing and using models to
provide scientific insights into weather and climate change, Qian and others
are striving to understand uncertainty in systems and modeling to improve projections
and help prepare vulnerable regions for potential climate change impact.

In Search of Better Models

Uncertainty quantification is also a focus for the U.S. Department of Energy (DOE) as eight
national laboratories and six partner institutions collaborate to develop and
apply the next generation of climate and Earth-system models to the challenges
and demands of climate-change research. DOE's
Accelerated Climate Modeling for Energy (ACME) project is focused on how
global water cycles, water resources, biogeochemical cycles, and rapidly
changing ice or snow interact with climate systems and climate change. The
research agenda of DOE's Office of Science (SC) includes the Scientific Discovery through Advanced Computing
(SciDAC) project addressing critical gaps in scientific computing and the
resources needed to fill them. The program supports research that enables
computing at extreme scales, as well as understanding extreme-scale data to
enhance the speed and accuracy of climate models and other scientific
calculations.

Scientific modeling and simulation have become crucial for
research problems that are insoluble by traditional theoretical and
experimental approaches that can be both time consuming and expensive. Information presented at the UQ workshop will
benefit both the SciDAC and ACME projects by providing more efficient
evaluation and calibration strategies for high-resolution models like ACME.

With support from multiple DOE SC projects, Qian and his
team at PNNL have published a dozen peer-reviewed papers in the past three
years regarding UQ methodologies and their application in regional and global
climate modeling. Topics have included sensitivity analysis, calibration, and
optimization for cloud and convection systems as well as aerosol processes. The
team is providing the scientific expertise and experience to help researchers
achieve the next milestones in climate modeling.